Triple
T7061379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Albury Airport |
E164222
|
entity |
| Predicate | hasLightingForNightOperations |
P13444
|
FINISHED |
| Object | yes |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: yes | Statement: [Albury Airport, hasLightingForNightOperations, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLightingForNightOperations Context triple: [Albury Airport, hasLightingForNightOperations, yes]
-
A.
isIlluminatedAtNight
Indicates that an entity receives or emits sufficient light to be visibly illuminated during nighttime conditions.
-
B.
hasLighting
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
-
C.
hasNightRaceLighting
Indicates that the subject facility or venue is equipped with lighting suitable for hosting events or activities at night.
-
D.
hasLightingEffect
Indicates that one entity applies, produces, or is associated with a particular lighting effect on another entity or environment.
-
E.
hasRunwayLighting
chosen
Indicates that a runway is equipped with lighting systems to aid visibility and operations, typically during low-light or night conditions.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c688796c148190adb2f1596f595f22 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e4a3c36c819080942c59f1830ae8 |
completed | March 27, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69c6e1bdc1f08190975fcdbbb1854d1e |
completed | March 27, 2026, 7:59 p.m. |
Created at: March 27, 2026, 2:38 p.m.